Open AccessBig Data: Big Data Analysis, Issues and Challenges and Technologies
Author(s) -
Romil Rawat,
Rishika Yadav
Publication year - 2021
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/1022/1/012014
Subject(s) - big data , data science , computer science , analytics , data analysis , unstructured data , process (computing) , data visualization , software analytics , visualization , data mining , software , software construction , software system , programming language , operating system
The data generated at an exponential rate has resulted in Big Data. This data has many characteristics and consists of structured, unstructured, and semi-structured data formats. It contains valuable information for the different types of stakeholders based on their need however it is not possible to meet them with the help of traditional tools and techniques. Here the big data technologies play a crucial role to handle, store, and process this tremendous amount of data in real-time. Big data analytics is used to extract meaningful information or patterns from the voluminous data. It can be further divided into three types i.e. text analytics, audio analytics, video analytics, and social media analytics. Big data analytics if followed by big data analysis process plays a significant role in generating meaningful information from big data. Big data analysis process consists of data acquisition, data storage, data management, data analytics, and finally data visualization. However, it is not simple and brings many challenges that need to be resolved. This paper presents the issues and challenges related to big data, prominent characteristics of big data, big data analytics, big data analysis process, and technologies used for processing the massive data.